2021 : DTM Generation Using Slope Based and Grid Based Filtering (Case Study: Wonokromo and Lontar Sub-District, Surabaya)

Hepi Hapsari Handayani ST.,M.Sc.,Ph.D



Published in


External link






The availability of accurate and accountable data, as well as community participation, is the key to planning and implementing sustainable development in the industrial era 4.0. Geospatial data and information that are provided accurately and detail can deliver a significant development impact. Local governments that have a sustainable development orientation need to be supported by the availability of one version of data that is accurate and accountable in order to making cities safe and sustainable. It means ensuring access to safe and affordable housing, and upgrading slum settlements. It also involves investment in public transport, creating green public spaces, and improving urban planning and management in a way that is both participatory and inclusive. The need for detailed geospatial data on a large scale is increasing, but the availability of existing base maps has not been able to meet this requirement. Topographic maps are the basic maps needed for geospatial analysis for the preparation of the urban land use plan. In addition, a topographic map is needed in the mapping of disaster-prone areas, planning and analysis of agriculture, plantations and mining, as well as detailed geological mapping. Herein, the geospatial information of terrain is vital. One of terrain elevation data is Digital Terrain Model (DTM). DTM is a digital terrain model that only contains ground level information (bare earth surface) without being affected by vegetation or other man-made features. While Digital Surface Model (DSM) is a representation of the earth's surface that contains more height information including all objects that are located on the surface of the earth such as vegetation, buildings, and other features. It is necessary to accelerate the provision of geospatial information, in this case DTM as an element of forming large-scale topographic maps. For this reason, a more effective DTM formation method is needed. The study was conducted to examine methods that can produce DTM automatically, in order to obtain a fast and efficient mapping method. In this study the method used are Slope Based Filtering (SBF) and Grid Based Filtering (GBF) method. Those approaches are applied in two different characteristics of study area. In the first area, which is a location that has characteristics of densely populated areas so that there are many buildings that coincide with each other, the area is located in Wonokromo Sub-District, South Surabaya. The second area has characteristics of open space with few settlements and a lot of barelands. The area is located in Lontar Village, West Surabaya. The results of the data processing based on two methods are then compared to the Stereoplotting DTM used as a reference. The comparison is performed as geomorphology analysis or visualization, and vertical geometry accuracy. The results of this study indicate that SBF method has a higher accuracy compared to the one of GBF. This is revealed by the results of the classification of data processing using eight parameters in each method. The average of RMS Error obtained in Wonokromo is smaller that is 0.605 meters compared to Lontar Village of 1.605 m. Wonokromo has an average map accuracy scale of 1: 2,500 while Lontar which has an average map accuracy class of 1: 5,000. Visually, the geomorphology produced from the SBF method is finer than the one of GBF.